地理实体具有对象化、结构化、语义化、机器可读等显著特征,具备业务语义的地理实体在自然资源业务审批、监管和决策分析中可以发挥重要的信息载体和联结纽带作用.语义化内容与应用需求密切相关,本文面向"三旧"改造成效评估业务,探索地理实体的语义化内容获取、表达及成果应用的实现路径,为"三旧"改造成效评估业务提供了新型解决思路,助力提升该项业务的精细化管理水平.
This paper addressed the focus of existing domestic research on the application issues of three-dimensional(3D)laser scanners in engineering by re-examining the development history of 3D laser scanners.The fundamental ranging principles of commonly used methods in 3D laser scanners,such as triangulation,phase ranging,and pulse ranging,were introduced.3D laser scanners were further classified into dynamic 3D laser scanners,static 3D laser scanners,and handheld 3D laser scanners,based on different carriers.To further leverage the value of 3D laser scanners,it is necessary to establish appropriate calibration standards for different types of instruments,ensuring that the accuracy of the devices meets the precision requirements of the objects being measured.In data processing,the development of improved software was essential to address the multipath effect and data void issues present in the measurement data.
As a bridge between remote sensing data and industry applications,remote sensing data processing software plays an irreplaceable role in the development of remote sensing industrialization in China.In order to reduce the dependence on foreign remote sensing data processing software at source and meet the growing national economic and security needs,it is necessary to carry out research on the application of domestic remote sensing software in the practical teaching of surveying and mapping majors and promote the use and development of domestic remote sensing software in surveying and mapping majors in colleges and universities.This paper analyzed the necessity and applicability of pixel information expert(PIE)domestic remote sensing data processing software in college teaching from the teaching needs of remote sensing practical courses of surveying and mapping undergraduate majors,made full use of experiential teaching concept and flipped classroom,designed relevant teaching cases and conducts experiments in undergraduate teaching practice,and provided important reference for the promotion and application of PIE in experiential practical teaching of surveying and mapping majors.At the same time,it provided an important reference to promote the development of domestic remote sensing software in practical teaching.
Aiming at the deformation monitoring problem of dam safety operation,this study of dam deformation detection method was carried out based on small baseline subset-interferometric synthetic aperture radar(SB AS-InS AR)technology.The dam differential interferometric phase diagram was generated by setting the time baseline threshold.The improved Goldstein filter algorithm was realized to filter the differential interferometric phase diagram of the dam.Using the minimum discontinuous region growth unwinding algorithm,the phase unwinding dam differential interferometric phase diagram was presented.The high coherence points were selected in the dam phase unwinding diagram by the coherence coefficient threshold method.The mathematical model of elevation measurement and estimation for dam deformation detection and monitoring was established.Through the singular value decomposition method,the mathematical model was solved to realize the dam detection and monitoring results.Experiments showed that the method could generate dam differential interferogram effectively and remove the internal noise of dam differential interferogram.It could effectively detect and monitor the shape variables of each monitoring point in the dam.
In view of the shortage that the optical forest canopy gap rate extraction method is greatly affected by weather,this paper proposed a three-dimensional volumetric model method for forest canopy extraction based on light detection and ranging(LiDAR)point cloud data,and used point cloud projection and DHP for comparison.The results showed that the variation trend of gap rate extracted from different volume cell sizes was basically the same.The larger the volume cell size was,the smaller the gap rate extracted was.When compared with point cloud projection and DHP,the correlation between the extracted results of the proposed method and those of the two methods gradually increased with the increase of the volume element.When the top Angle was 0°～80° and 10°～65°,the correlation coefficient was above 0.91,indicating that the proposed method could be used to extract the forest canopy gap ratio.
In the complex marine ecological environment,with the increase of the service life of submarine pipelines,the phenomenon of exposed and suspended diseases of submarine pipelines is obvious,which seriously threatens the safety of offshore oil production.In order to accurately evaluate the development degree of the suspension of the sea pipe and guide the construction of the treatment project.The remotely operated vehicle(ROV)was equipped with a multi-beam echo sounder to carry out short-distance detection.The exact position,height and length of the suspended section of the submarine pipeline were determined,the treatment of suspended rocks was guided,and the treatment effect was evaluated.The results showed that the ROV equipped with a multi-beam depth sounder could get close to the pipeline at a close distance,complete refined detection,avoid the influence of sea waves and tidal surges on multi-beam detection,and more accurately evaluate the degree of disease and guide the construction of treatment.
2023年8月30日北京测绘学会举办了2023年"探寻北斗之旅"主题科普活动.此次活动组织相关事业单位职工及子女、北京市测绘设计研究院新入职职工等80余人,在北京房山人卫激光国家野外科学观测研究站开展科普活动.
Given the fact that Gaofeng-3(GF-3)synthetic aperture radar(SAR)can capture the wind streak whose gray values are changing in black and white on image,a wind retrieval method based on Sobel gradient operator is proposed to retrieve wind field from GF-3 SAR images.After resampling the SAR image,the Sobel gradient operator was applied to calculate the wind direction over the sea surface,and then an extended CMOD5 scattering model was explored to calculate the wind speed.To test this method,an experiment was done to process the GF-3 SAR image,whose retrieved wind field is then evaluated using the European Centre for Medium-Range Weather Forecasts(ECMWF)reanalysis wind field data and National Data Buoy Center(NDBC)buoy wind vector.The experiment showed that compared with the ECMWF reanalysis wind field,the root mean square error of the retrieved SAR wind speed and direction was 1.79 m/s and 11.95°,respectively,while compared to NDBC buoy data,the absolute deviation of wind speed and direction was 0.24 m/s and 9.03°,respectively.Therefore,the proposed method acted well to retrieved wind filed with higher precision from GF-3 SAR images.The research results could provide a reference for the wind field retrieval technology of GF-3 SAR.
According to the requirements for the construction of national land survey database,this study proposed a method for identifying the narrow and long vector patches in national land survey.The raster values were calculated by rasterizing the vector patches and performing evolutionary calculations based on their shape features.To achieve a rapid identification of narrow and long vector patches,the narrow and non-narrow areas within the vector patches were differentiated according to the raster values.The identification method proposed in this study could avoid unpredictable factors caused by the topological problems of vector graphics and could improve the accuracy of the identification of the narrow and long vector patches in national land survey,providing an important technical support for the construction of national land survey database.
As the deep learning-based target detection model becomes more and more mature,it has become an important research direction to deploy the target detection model to aerial unmanned aerial vehicle(UAV).Aiming at the limited computing power and memory of the onboard reasoning equipment of UAV,a structural reparameterized you only look once V5(YOLOV5)aerial target detection model was proposed.Firstly,the feature extraction network of the YOLOV5 model was replaced as the structurally reconfigurable network.Then,the multi-branch YOLOV5 model was trained with the help of the open source data set.Then,the multi-branch network was reparameterized to obtain the single-path network model.The experiment showed that the reasoning speed of the reparametric YOLOV5 model increased by about 3 times,the detection rate increased by 0.03％,the recall rate increased by 0.02％,and the mAP0.5 increased by 1.22.
Uneven land subsidence has a far-reaching and difficult to recover impact on urban planning and development,and will have a huge impact on society and people's property when it is serious.To solve this problem,this paper collected and collated the first and second order leveling monitoring data covering Tianjin for two consecutive years in 2020 and 2021,and used the observation data of continuous GNSS monitoring stations as prior observations for dynamic adjustment.The annual settlement calculation results and the high-resolution Radarsat-2(R2)SAR image data processing results were fused with the trend surface fitting method to calculate the land subsidence in Tianjin in 2021.The calculation results were compared with the settlement observation data processing results over the years,and the land subsidence in Tianjin was analyzed.It provided a reference for Tianjin to formulate relevant planning,refined sediment control management and improved governance measures.
In view of the difficulties in classification of road point cloud data obtained by vehicular laser scanning,this paper proposed a road surface extraction method based on Otsu algorithm and improved region growth algorithm.The filtering of non-ground points in the original point cloud depended on Otsu algorithm to adaptively calculate the segmentation threshold;Then calculate the normal vector and curvature of the point cloud respectively;Finally,the normal vector similarity wsa used as a constraint condition,and the improved region growth algorithm was applied to extract the road surface accurately.Taking the point cloud data of two typical urban roads as an example,The test results showed that the accuracy CR,integrity CP and extraction quality Q of the road surface results extracted by this method were more than 94％,which fully proved the effectiveness of this method.
In order to solve the problem of low positioning accuracy caused by non line-of-sight propagation patterns of satellite navigation positioning signals due to occlusion,an improved Kalman filter based optimization method for satellite navigation positioning accuracy was studied.Improve the optimization settings of the leapfrog algorithm,optimize support vector machines,and classify and extract satellite navigation signals with occlusion information;Design a satellite navigation positioning accuracy improvement algorithm based on improved Kalman filtering,dynamically estimate the covariance of satellite navigation signal observation noise with occlusion information,adaptively adjust the signal filtering gain,comprehensively remove invalid positioning information from the signal,and obtain accurate satellite navigation positioning results.The research results show that after using the proposed method,the actual position of satellite navigation and positioning results are highly matched,and the positioning accuracy is significantly improved.
Traditional Topographic map survey methods are time-consuming and laborious.In this paper,it takes the phase topographic mapping project of BYD factory in Fuzhou as an example,oblique photography and light detection and ranging(LiDAR)point cloud technology were merged.The aerial survey technology of airborne LiDAR was used in non-house area,and the aerial survey technology of oblique photogrammetry was used in house area.Finally,through the field collection checkpoint and indoor mapping results for comparative analysis of accuracy.The result showed that the plane and elevation could meet the precision requirement of large-scale mapping,and it could save the time and cost of topographic mapping.
The baseline vector is calculated by using the observation data collected by global navigation satellite system(GNSS)receiver with random software or commercial and special software.The three-dimensional coordinate difference between the receivers,baseline vector is the result of relative positioning,it is the observation of control network adjustment,and the quality of baseline vector affects the adjustment result of control network.The control network should check the quality of baseline vector before unconstrained and constrained adjustment.The purpose of the inspection is to eliminate gross errors and baselines whose baseline solutions are out of limit.Through the calculation of a C-level network,it was found that the result of constrained adjustment without baseline check was higher than that of constrained adjustment with baseline check.Through the analysis of the calculation process of point-to-point error,it could be concluded that with the increase of baseline vector,virtual high point-to-point error will sometimes be obtained without baseline check.The point error of GNSS control network can not fully reflect the accuracy of the network,but the error in unit weight can better reflect the accuracy check of the network.It is necessary to check the baseline of GNSS control network before unconstrained and constrained adjustment.
Aiming at the problems of traditional homomorphic filtering for uniform light and color algorithm for unmanned aerial vehicle(UAV)image,such as multiple uncertain parameters in transfer function and serious color distortion in uniform light and color effect,this paper proposed a uniform light and color method for UAV image based on improved homomorphic filtering.In this algorithm,a new transfer function with fewer parameters was constructed,and the transfer function was applied to the homomorphic filtering algorithm.The improved homomorphic filtering algorithm was used to evenly process each component of RGB in UAV images.Experimental results showed that the proposed algorithm was better than the traditional homomorphic filtering algorithm.
With the rapid development of economy,shallow surface movement in urban areas has become the focus of current research.In this paper,small baseline subset interferometric synthetic aperture radar was applied to process 36 scene Sentinel-1 data in Guangzhou-Foshan region from October 2018 to April 2022,and GACOS product was introduced to assist atmospheric correction to obtain the time series deformation of the study area.The results showed that the average annual deformation rate was mainly in the range of-4.9～5.9 mm/a,and the subsidence was scattered,mainly in the west of Chancheng district,the north of Shunde district and Nansha district in the study area.The subsidence along the subway line in the study area was mainly in the local area of Foshan Line 2,Guangzhou Line 2 and Line 3.
Illegal construction has seriously affected the appearance of the city and the lives of residents.In order to effectively monitor and discover illegal construction,this paper explored and practiced the key technology of illegal construction monitoring based on street view data,and carried out a demonstration application in Beijing,forming the following research results:① the technology of street view technology was developed in monitoring illegal construction Process;②deep learning technology was integrated to develop an automatic recognition algorithm for changing buildings in street view,design the layout format of the change map and propose an automatic generation algorithm for the change map;③Combining geographic information system(GIS)technology,an on-site inspection of illegal construction integrated with internal and external industries business process was formed to realize the whole process monitoring of illegal construction from discovery to demolition;④the street view violation inspection system was researched and designed to carry out practical application in the special action of"decommissioning,rectification and promotion"in Beijing.The key technology research and application demonstration in this paper have important technical support for improving the construction of the city's ecological civilization and the spatial governance of the city's appearance and city appearance.
A comprehensive grasp of the health status of the drainage pipe network of the newly built residential area is one of the important contents of urban stormwater diversion transformation,which can provide a basis for urban planning,construction,follow-up custody and maintenance,and the formulation of pipe network maintenance and repair plans.From the perspective of actual production and application,this paper proposed a method for drainage pipe network acceptance based on CCTV detection technology,aiming at the problems of"through-ball test"and many hidden points in drainage pipe section in traditional new residential drainage pipe network acceptance,and obtained a feasible drainage pipeline data collection and acceptance scheme.Taking some newly built residential areas in Jinan as the research object,the five aspects of rainwater sewage diversion,municipal connection,pipeline structural condition,pipeline functional condition and manhole and rainwater outlet were tested,and the risk points of rainwater mixed connection and the influencing factors of pipeline defects were summarized and analyzed,which proved the feasibility and effectiveness of using CCTV detection technology for drainage pipe network acceptance,and provided reference for the acceptance of drainage pipe network in other cities.
The detailed investigation of geological disasters is an important work to carry out mass prevention and collective strategy and ensure the safety of people's lives and property,and the study of the law of geological disasters is of great significance to the comprehensive prevention and control of geological disasters.Taking a county in the mountainous area of northern Guangdong as an example,the distribution law and influencing factors of geological disasters in the study area were discussed by using geostatistical methods and the spatial analysis function of ArcGIS software.The results indicated that:①The Moran I index in the study area was 0.949,the occurrence time of geological disasters coincided with the rainfall time,and the spatial distribution tended to be concentrated and obvious in terms of regionality;②The geological disasters in the study area were mainly small and medium-sized soil landslides and collapses,and the large-scale slope construction and road construction by local residents were the main human driving factors.Rainfall is an important cause of geological disasters,and the influence of human engineering activities on geological disasters cannot be ignored.
